摘要
Network topology optimization has been widely researched. Since market competition has gradually developed into competition among the supply chain information systems, the network to- pology optimization of supply chain information systems has been in urgent need. However, the net- work topology optimization of supply chain information systems is still in its early stages and still has some challenges. So a description of typical seven network topologies for various supply chain infor- mation systems has been given. The generic characteristics of each network topology can be summa- rized. To analyze the optimization of network topology optimization of supply chain information sys- tems, a numeric model has been established based on these general characteristics. A genetic algo- rithm is applied in the network topology optimization of supply chain information systems model to a- chieve the minimum cost and shortest path. Finally, our experiment results are provided to demon- strate the robustness and effectiveness of the proposed model.
Network topology optimization has been widely researched. Since market competition has gradually developed into competition among the supply chain information systems, the network to- pology optimization of supply chain information systems has been in urgent need. However, the net- work topology optimization of supply chain information systems is still in its early stages and still has some challenges. So a description of typical seven network topologies for various supply chain infor- mation systems has been given. The generic characteristics of each network topology can be summa- rized. To analyze the optimization of network topology optimization of supply chain information sys- tems, a numeric model has been established based on these general characteristics. A genetic algo- rithm is applied in the network topology optimization of supply chain information systems model to a- chieve the minimum cost and shortest path. Finally, our experiment results are provided to demon- strate the robustness and effectiveness of the proposed model.
基金
Supported by the National Natural Science Foundation of China(61202363,U1261203)
